This disclosure relates to system and method of detecting particulate matter throughout a particulate matter sensor measurement cycle.
Rich combustion conditions, such as those which occur in diffusion flame processes that are present in diesel engines and other internal combustion engines, produce particulate matter, which is carried in its exhaust stream. Particulate matter emissions are typically limited by emissions regulations and it is common for modern diesel engines to be equipped with a particulate filter. As part of the emissions regulations, diagnosis of the particulate filter is mandated and the use of a particulate matter sensor is one such diagnostic system. Thus, it is desirable to accurately measure particulate matter real-time in vehicles to ensure that the engine and particulate filter are operating in compliance with government regulations. It is also desirable to measure particulate matter using emissions testing equipment during engine development on a dynamometer, for example.
One type of particulate matter sensor includes electrodes that are closely spaced on an electrically non-conductive substrate. As particulate matter accumulates between the electrodes, the sensor's electric resistance decreases as the initially non-conductive substrate surface between electrodes becomes gradually more electrically conductive due to the deposited particulate matter (PM) or soot, which is indicative of the amount of particulate matter in the sensed exhaust pipe, either directly produced by the combustion process or its remnants escaping the action of the particulate filter.
During the measurement cycle, a typical particulate matter sensor only measures soot during an active zone. Once a predetermined threshold has been reached, which corresponds to the sensor being saturated with soot to a pre-defined extent, the sensor undergoes regeneration to prepare the sensor to again measure the accumulation of soot. Subsequent to regeneration and prior to reaching the active zone, the sensor has a deadband zone in which there has been no measurement of soot due to the very small change in conductance within the sensor during the initial soot deposition period. Instead, a sensor measurement controller utilizes the sensor response time (the time span between the end of sensor regeneration to the subsequent start of sensor regeneration) as the output parameter indicating the level of soot in the exhaust stream. The engine ECM receives this time interval, compares this time interval to a calibration table, and calculates a corresponding pass/fail diagnostic determination.
This particulate matter measurement method has several drawbacks including a long response time (possibly tens or hundreds of minutes for low soot level conditions), provides only a time-integrated output with no real-time response, and provides no direct measure of soot level, only a measure of time interval which requires the customer to interpret the results via a calibration table to compensate for exhaust velocity and flow area. As particulate matter begin to deposit, they are sparse and their deposition causes undetectable change in sensor resistance due, in part, to the presence of a bias resistor in the sensor's circuit (used for diagnosing the sensor itself), which causes the deadband zone. Previously, deadband time had been ignored by the ECM and was considered an undesirable characteristic of the sensor design.
Diesel particulate filter diagnostic decisions, for example, must be made during one Federal Test Procedure drive cycle, which is approximately 11 miles and 31 minutes in length.
Additionally, experimentally observed step-like unusual changes in the measured particulate matter deposit resistance are commonly attributed to either occasional bombardment of the sensor surface with particles much larger than the typical size within the particles' size distribution, or losses of already-deposited particle mass due to blow-offs. This dramatic alteration of particulate matter resistance gradient measured in the time domain corrupts the particulate matter concentration assessment algorithm which may be based on the measure of the cycle time, i.e., time markers representing arbitrarily selected sensor resistances indicating the start of sensing cycle and its end. These error effects are explained in, for example, “Sensing of Particulate Matter for On-Board Diagnosis of Particulate Filters”, H. Husted et al, SAE Int. J. Engines 5(2) (2012).
There is a need to obtain and interpret accurate readings from the particulate matter sensor as often as possible and quickly calculate particulate matter mass, concentration and flux based on sensor output.